Staff Machine Learning Engineer, Financial Products

About the Position

Staff Machine Learning Engineer, Financial Products

San Francisco

This is Adyen.

Adyen provides payments, data, and financial products in a single solution for customers like Meta, Uber, H&M, and Microsoft - making us the financial technology platform of choice. At Adyen, everything we do is engineered for ambition.

For our teams, we create an environment with opportunities for our people to succeed, backed by the culture and support to ensure they are enabled to truly own their careers. We are motivated individuals who tackle unique technical challenges at scale and solve them as a team. Together, we deliver innovative and ethical solutions that help businesses achieve their ambitions faster.

Financial Products

About the Role

The Financial Products org at Adyen is at the forefront of our evolution, building the foundational infrastructure that enables our customers to manage their finances, issue cards, and access credits and financing globally. Adyen is building a Machine Learning Engineering team in San Francisco focused on Credit Risk Modeling for Underwriting within Financial Products. This team will develop the models, scorecards, and production systems that enable Adyen to scale its credit products 100x.

As a Staff Machine Learning Engineer you will design, productionize, and operate machine learning models and rule-based decision systems that power credit products. You will work across the full model lifecycle, from research and data analysis to training, deployment, monitoring, and continuous improvement.

This role is ideal for an engineer who combines strong machine learning and production engineering experience with sound judgment in high-integrity financial systems. You will help build continuous data flywheels that improve underwriting decisions while balancing rapid product innovation with robustness, explainability, and global scale.

We are looking for engineers with a customer-problem-first mindset and experience building reliable ML systems in production. You will work closely with product, engineering, risk, and data teams to deliver underwriting capabilities for some of the world’s leading businesses.

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Responsibilities

• Develop and maintain scalable production ML pipelines for feature engineering, model training, validation, and deployment. Examples ML domains are: supervised and semi-supervised learning methods for inference on credit risk patterns;
• Identify and fix performance bottlenecks in ML training and inference (memory consumption, online latency, training time etc.);
• Collaborate with software engineers to integrate ML solutions into products and services;
• Collaborate with CreditOps and data teams to integrate effectively with current tools, and shape priority for future tools;
• Support and encourage good engineering practices on product ML teams;

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Requirements

• 8+ years of experience as an engineer working in the machine learning domain;
• Strong Python programmer and experience in Java;
• Experience with the full machine learning model lifecycle in production flows;
• Experience leveraging big data to create the pipelines needed to feed the models with appropriate data;
• Strong understanding of good software engineering practices as well as data engineering and MLOps principles;
• Knowledge of data science, statistics, and machine learning techniques;
• Familiarity with the standard data science toolkit in Python, such as (py)spark, (Trino) SQL, Tensorflow, PyTorch, XGBoost/LightGBM, Pandas, MLFlow or similar MLOps frameworks, and Airflow;
• Knowledge/experience of working with ML infrastructure components with tools such as k8s, docker, airflow, argo-workflows, prometheus, grafana;
• Experimental mindset with a launch fast and iterate mentality;
• Proactively take the lead in projects, from ideation to deployment. Experience working with a wide range of stakeholders and can clearly communicate complex outcomes over a wide range of audiences.

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Nice to Have

• Experience on underwriting models or systems;
• Experience working with a Machine Learning ‘Feature Store’.

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We Offer

• Competitive salary range of $297,000 - $401,000 plus RSUs;
• Opportunity to work in a solid, established company with a startup mindset;
• Direct access to massive global datasets (e.g., payments, identity data);
• Environment of ownership and speed, where a focused research team can make a significant difference;
• Be at the forefront of bridging ML and fintech, shaping how these two critical areas intersect;
• Flexibility for future relocation to our offices in Amsterdam or Madrid if it better supports your personal or professional goals.

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About the Company

Our unique approach is a product of our diverse perspectives. This diversity of backgrounds and cultures is essential in helping us maintain our momentum. Our business and technical challenges are unique, and we need as many different voices as possible to join us in solving them - voices like yours. No matter who you are or where you’re from, we welcome you to be your true self at Adyen.

Adyen is an equal opportunity employer. We do not discriminate based on race, color, ethnicity, ancestry, national origin, religion, sex, gender, gender identity, gender expression, sexual orientation, age, disability, veteran status, genetic information, marital status, or any legally protected status.

All your information will be kept confidential according to EEO guidelines.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

This role is based out of our San Francisco office. We are an office-first company and value in-person collaboration; we do not offer remote-only roles.